feat(models): add Runcrate as an OpenAI-compatible provider

examples/smart_scraper_graph/runcrate/smart_scraper_runcrate.py

@@ -0,0 +1,47 @@
+"""
+Basic example of scraping pipeline using SmartScraper with Runcrate
+"""
+
+import json
+import os
+
+from dotenv import load_dotenv
+
+from scrapegraphai.graphs import SmartScraperGraph
+from scrapegraphai.utils import prettify_exec_info
+
+load_dotenv()
+
+# ************************************************
+# Define the configuration for the graph
+# ************************************************
+
+
+graph_config = {
+    "llm": {
+        "api_key": os.getenv("RUNCRATE_API_KEY"),
+        "model": "runcrate/deepseek-ai/DeepSeek-V4.1-Flash",
+    },
+    "verbose": True,
+    "headless": True,
+}
+
+# ************************************************
+# Create the SmartScraperGraph instance and run it
+# ************************************************
+
+smart_scraper_graph = SmartScraperGraph(
+    prompt="Extract me the first article",
+    source="https://www.wired.com",
+    config=graph_config,
+)
+
+result = smart_scraper_graph.run()
+print(json.dumps(result, indent=4))
+
+# ************************************************
+# Get graph execution info
+# ************************************************
+
+graph_exec_info = smart_scraper_graph.get_execution_info()
+print(prettify_exec_info(graph_exec_info))

scrapegraphai/graphs/abstract_graph.py

@@ -13,7 +13,7 @@
 from pydantic import BaseModel
 
 from ..helpers import models_tokens
-from ..models import XAI, CLoD, DeepSeek, MiniMax, Nvidia, OneApi
+from ..models import XAI, CLoD, DeepSeek, MiniMax, Nvidia, OneApi, Runcrate
 from ..utils.logging import get_logger, set_verbosity_info, set_verbosity_warning
 
 logger = get_logger(__name__)
@@ -175,6 +175,7 @@ def _create_llm(self, llm_config: dict) -> object:
             "togetherai",
             "xai",
             "minimax",
+            "runcrate",
         }
 
         if "/" in llm_params["model"]:
@@ -243,6 +244,7 @@ def _create_llm(self, llm_config: dict) -> object:
                 "clod",
                 "xai",
                 "minimax",
+                "runcrate",
             }:
                 if llm_params["model_provider"] == "bedrock":
                     llm_params["model_kwargs"] = {
@@ -263,6 +265,9 @@ def _create_llm(self, llm_config: dict) -> object:
                 if model_provider == "minimax":
                     return MiniMax(**llm_params)
 
+                if model_provider == "runcrate":
+                    return Runcrate(**llm_params)
+
                 if model_provider == "ernie":
                     from langchain_community.chat_models import ErnieBotChat
 

scrapegraphai/helpers/models_tokens.py

@@ -352,6 +352,14 @@
         "gpt-5.4-mini": 400000,
         "gpt-5.4": 1000000,
     },
+    "runcrate": {
+        "deepseek-ai/DeepSeek-V4.1-Flash": 1048576,
+        "zai-org/GLM-5.3": 1048576,
+        "zai-org/GLM-5.3-Flash": 1048576,
+        "Qwen/Qwen3.8-Flash": 1000000,
+        "openai/gpt-oss-120b": 131072,
+        "moonshotai/Kimi-K2.6": 262144,
+    },
     "deepseek": {
         "deepseek-chat": 128000,
         "deepseek-coder": 128000,

scrapegraphai/models/__init__.py

@@ -11,6 +11,7 @@
 from .oneapi import OneApi
 from .openai_itt import OpenAIImageToText
 from .openai_tts import OpenAITextToSpeech
+from .runcrate import Runcrate
 from .xai import XAI
 
-__all__ = ["AtlasCloud", "CheaperInference", "DeepSeek", "MiniMax", "OneApi", "OpenAIImageToText", "OpenAITextToSpeech", "CLoD", "XAI", "Nvidia"]
+__all__ = ["AtlasCloud", "CheaperInference", "DeepSeek", "MiniMax", "OneApi", "OpenAIImageToText", "OpenAITextToSpeech", "Runcrate", "CLoD", "XAI", "Nvidia"]

scrapegraphai/models/runcrate.py

@@ -0,0 +1,23 @@
+"""
+Runcrate Module
+"""
+
+from langchain_openai import ChatOpenAI
+
+
+class Runcrate(ChatOpenAI):
+    """
+    A wrapper for ChatOpenAI configured for Runcrate's OpenAI-compatible
+    inference API. Model ids keep their vendor prefix, for example
+    ``deepseek-ai/DeepSeek-V4.1-Flash``.
+
+    Args:
+        llm_config (dict): Configuration parameters for the language model.
+    """
+
+    def __init__(self, **llm_config):
+        if "api_key" in llm_config:
+            llm_config["openai_api_key"] = llm_config.pop("api_key")
+        llm_config["openai_api_base"] = "https://api.runcrate.ai/v1"
+
+        super().__init__(**llm_config)

tests/test_runcrate_model.py

@@ -0,0 +1,31 @@
+"""Tests for the Runcrate model configuration."""
+
+from unittest.mock import Mock, patch
+
+from scrapegraphai.graphs import SmartScraperGraph
+from scrapegraphai.models import Runcrate
+
+
+def test_runcrate_model_sets_openai_compatible_base_url():
+    """Runcrate should map api_key and pin its base URL."""
+    model = Runcrate(api_key="test-key", model="deepseek-ai/DeepSeek-V4.1-Flash")
+
+    assert str(model.openai_api_base).rstrip("/") == "https://api.runcrate.ai/v1"
+    assert model.openai_api_key.get_secret_value() == "test-key"
+
+
+def test_runcrate_provider_keeps_vendor_prefixed_model_id():
+    """`runcrate/<vendor>/<model>` resolves to Runcrate with the full model id."""
+    config = {
+        "llm": {
+            "model": "runcrate/deepseek-ai/DeepSeek-V4.1-Flash",
+            "api_key": "test-key",
+        }
+    }
+    with patch.object(SmartScraperGraph, "_create_graph", return_value=Mock(nodes=[])):
+        graph = SmartScraperGraph("prompt", "https://example.com", config)
+
+    assert isinstance(graph.llm_model, Runcrate)
+    assert graph.llm_model.model_name == "deepseek-ai/DeepSeek-V4.1-Flash"
+    assert graph.model_token == 1048576
+    assert not getattr(graph, "model_tokens_defaulted", False)